Babysitter Survey Design

Design and analyze surveys for product validation and user research

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/product-management/skills/survey-design" ~/.claude/skills/a5c-ai-babysitter-survey-design && rm -rf "$T"

manifest: library/specializations/product-management/skills/survey-design/SKILL.md

Survey Design Skill

Overview

Specialized skill for designing and analyzing surveys for product validation. Enables product teams to gather structured feedback through well-designed surveys and interpret results with statistical rigor.

Capabilities

Survey Design

Design PMF surveys (Sean Ellis test)
Create NPS survey implementations
Build feature validation surveys
Generate survey question banks
Design onboarding feedback surveys
Create churn exit surveys

Question Engineering

Write unbiased survey questions
Design appropriate response scales
Create skip logic and branching
Optimize question order
Balance survey length vs completion

Analysis

Analyze survey response data
Calculate statistical confidence in results
Segment analysis by user attributes
Identify response patterns and themes
Generate actionable insights from data

Target Processes

This skill integrates with the following processes:

```
product-market-fit.js
```
- PMF survey design and analysis
```
beta-program.js
```
- Beta participant surveys
```
customer-advisory-board.js
```
- CAB feedback collection
```
jtbd-analysis.js
```
- Jobs-based survey questions

Input Schema

{
  "type": "object",
  "properties": {
    "surveyType": {
      "type": "string",
      "enum": ["pmf", "nps", "csat", "feature-validation", "exit", "onboarding", "custom"],
      "description": "Type of survey to design"
    },
    "objective": {
      "type": "string",
      "description": "Primary objective of the survey"
    },
    "targetAudience": {
      "type": "string",
      "description": "Target survey respondents"
    },
    "hypotheses": {
      "type": "array",
      "items": { "type": "string" },
      "description": "Hypotheses to validate through survey"
    },
    "maxQuestions": {
      "type": "number",
      "default": 10,
      "description": "Maximum number of questions"
    },
    "responseData": {
      "type": "array",
      "description": "Survey response data for analysis (if analyzing existing survey)"
    }
  },
  "required": ["surveyType", "objective"]
}

Output Schema

{
  "type": "object",
  "properties": {
    "survey": {
      "type": "object",
      "properties": {
        "title": { "type": "string" },
        "introduction": { "type": "string" },
        "questions": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "id": { "type": "string" },
              "type": { "type": "string" },
              "text": { "type": "string" },
              "options": { "type": "array", "items": { "type": "string" } },
              "required": { "type": "boolean" },
              "logic": { "type": "object" }
            }
          }
        },
        "estimatedTime": { "type": "string" }
      }
    },
    "analysisFramework": {
      "type": "object",
      "properties": {
        "keyMetrics": { "type": "array", "items": { "type": "string" } },
        "segmentationCriteria": { "type": "array", "items": { "type": "string" } },
        "successThresholds": { "type": "object" }
      }
    },
    "analysis": {
      "type": "object",
      "description": "Analysis results if response data was provided",
      "properties": {
        "responseRate": { "type": "number" },
        "keyFindings": { "type": "array", "items": { "type": "string" } },
        "segmentInsights": { "type": "object" },
        "statisticalConfidence": { "type": "object" },
        "recommendations": { "type": "array", "items": { "type": "string" } }
      }
    }
  }
}

Usage Example

const survey = await executeSkill('survey-design', {
  surveyType: 'pmf',
  objective: 'Measure product-market fit for new analytics feature',
  targetAudience: 'Active users who have used analytics at least 3 times',
  hypotheses: [
    'Users find the analytics feature valuable for their workflow',
    'Users would be disappointed if the feature was removed'
  ],
  maxQuestions: 8
});

Dependencies

Survey platform integrations
Statistical analysis libraries